To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse — definitions of classes, relations, functions, and other objects — is called an ontology. This paper describes a mechanism for defining ontologies that are portable over representation systems. Definitions written in a standard format for predicate calculus are translated by a system called Ontolingua into specialized representations, including frame-based systems as well as relational languages. This allows researchers to share and reuse ontologies, while retaining the computational benefits of specialized implementations. We discuss how the translation approach to portability addresses several technical problems. One problem is how to accommodate the stylistic and organizational differences among representations while preserving declarative content. Another is how to translate from a very expressive language into restricted languages, remaining system-independent while preserving the computational efficiency of implemented systems. We describe how these problems are addressed by basing Ontolingua itself on an ontology of domain-independent, representational idioms.

Reusable ontologies are becoming increasingly important for tasks such as information integration, knowledge-level interoperation, and knowledgebase development. We have developed a set of tools and services to support the process of achieving consensus on common shared ontologies by geographically distributed groups. These tools make use of the worldwide web to enable wide access and provide users with the ability to publish, browse, create, and edit ontologies stored on an ontology server. Users can quickly assemble a new ontology from a library of modules. We discuss how our system was constructed, how it exploits existing protocols and browsing tools, and our experience supporting hundreds of users. We describe applications using our tools to achieve consensus on ontologies and to integrate information. The Ontolingua Server may be accessed through the URL http://ontolingua.stanford.edu/

An ontology is a set of definitions of content-specific knowledge representation primitives: classes, relations, functions, and object constants. Ontolingua is mechanism for writing ontologies in a canonical format, such that they can be easily translated into a variety of representation and reasoning systems. This allows one to maintain the ontology in a single, machine-readable form while using it in systems with different syntax and reasoning capabilities. The syntax and semantics are based on the KIF knowledge interchange format [11]. Ontolingua extends KIF with standard primitives for defining classes and relations, and organizing knowledge in object-centered hierarchies with inheritance. The Ontolingua software provides an architecture for translating from KIF-level sentences into forms that can be efficiently stored and reasoned about by target representation systems. Currently, there are translators into LOOM, Epikit, and Algernon, as well as a canonical form of KIF. This paper describes the asic approach of Ontologia to the ontology sharing problem, introduces the syntax, and describes the semantics of a few ontological commitments made in the software. Those commitments, that are reflected in the ontological syntax and the primitive vocabulary of the frame ontology, include: a distinction between definitional and nondefinitional assertions; the organization of knowledge with classes, instances, sets, and second-order relations; and assertions whose meaning depends on the contents of the knowledge base. Limitations of Ontologia's "conservative" approach to sharing ontologies and alternative approaches to the problem are discussed.

Most enterprises agree that knowledge is an essential asset for success and survival on a increasingly competitive and global market. This awareness is one of the main reasons for the exponential growth of knowledge management in the past decade. Our approach to knowledge management is based on ontologies, and makes knowledge assets intelligently accessible to people in organizations. Most company-vital knowledge resides in the heads of people, and thus successful knowledge management does not only consider technical aspects, but also social ones. In this paper, we describe an approach to intelligent knowledge management that explicitly takes into account the social issues involved. The proof of concept is given by a large-scale initiative involving knowledge management of a virtual organization.

Information integration is enabled by having a precisely defined common terminology. We call this combination of terminology and definitions an ontology. We have developed a set of tools and services to support the process of achieving consensus on such a common shared ontologies by geographically distributed groups. These tools make use of the world-wide web to enable wide access and provide users with the ability to publish, browse, create, and edit ontologies stored on an ontology server. Users can quickly assemble a new ontology from a library of modules. We discuss how our system was constructed, how it exploits existing protocols and browsing tools, and our experience supporting hundreds of users. We describe applications using our tools to achieve consensus on ontologies and to integrate information.

The Ontolingua ontology development environment provides a suite of ontology authoring tools and a library of modular reusable ontologies. The environment is available as a World Wide Web service and has a substantial user community. The tools in Ontolingua are oriented toward authoring of ontologies by assembling and extending ontologies obtained from the library. In this paper, we describe Ontolingua's formalism for combining the axioms, definitions, and non-logical symbols of multiple ontologies. We also describe Ontolingua's facilities that enable renaming of non-logical symbols from multiple component ontologies and that disambiguate symbol references during input and output. These features of Ontolingua support cyclic inclusion graphs and enable users to extend ontologies in multiple ways such as adding simplifying assumptions and extending the domains of polymorphic operators. Introduction Explicit specifications of domain conceptualizations, called ontologies, are essential fo...

We describe an ongoing project to develop technology that will support collaborative construction and effective use of distributed large-scale repositories of highly expressive reusable ontologies. We are focusing on developing a distributed server architecture for ontology construction and use, representation formalisms that remove key barriers to expressing essential knowledge in and about ontologies, ontology construction tools, and tools for obtaining domain models for use in applications from large-scale ontology repositories. We are building on the results of the DARPA Knowledge Sharing Effort, specifically by using the Knowledge Interchange Format (KIF) as a core representation language and the Ontolingua system as a core ontology development environment. In order to enable distributed ontology repositories and services, we are developing a distributed server architecture for ontology construction and use based on ontology servers which provide access via a network API to the ...

Abstract: RDF-based tools promise to provide a base for reasoning about metadata and about situated data—data describing entities situated in time and space—that is superior to alternatives such as relational databases or object-oriented databases. However, essential representational machinery is missing from the current generation of Semantic Web tools and languages. When that machinery is added, the resulting capabilities offer a combination of novelty and flexibility that may usher in a wave of commercial Semantic Web tool-based applications that precedes the true arrival of the Semantic Web. We have constructed a system, the Semantic Engineering Workbench (SEW), that is proficient at managing situated data. Achieving a practical implementation necessitated extending the basic RDF tools (Hewlett-Packard’s Jena and Stanford’s Protégé) to support contexts. In the SEW, a context references a set of statements having common spatial, temporal (and other metadata) attributes. We investigated multiple possible implementations of contexts, and found significant drawbacks in the most common approaches. The clear winners are quads (adding a fourth field of type ‘context ’ to each triple results in a quadruple, or quad), and object-oriented contexts (a context mechanism that references individuals instead of statements). Most existing Semantic Web tools (e.g., Jena and Protégé) do not understand contextualized data. For these tools, object-oriented

Data and knowledge exchange among users of urban information systems presents many challenges. This paper discusses issues related to the use of ontologies in the development of urban geographic information systems and proposes the creation of software components from diverse ontologies as a way to share knowledge and data. These software components are derived from ontologies using an object-oriented mapping. The translation of an ontology into an active information system component leads to ontology-driven information systems and, in the specific case of geographic applications, to ontologydriven geographic information systems. We analyze the urban environment from the ontologists' point of view and make some inferences about the relationship between knowledge and data sharing, and the theory of bona fide and fiat objects. We also discuss implementation issues, such as the use of Ontolingua as an ontology editor, and CORBA IDL generator, CORBA, and Java as object platforms.

Data and knowledge exchange among users of urban information systems presents many challenges. This paper discusses issues related to the use of ontologies in the development of urban geographic information systems and proposes the creation of software components from diverse ontologies as a way to share knowledge and data. These software components are derived from ontologies using an object-oriented mapping. The translation of an ontology into an active information system component leads to ontology-driven information systems and, in the specific case of geographic applications, to ontologydriven geographic information systems. We analyze the urban environment from the ontologists' point of view and make some inferences about the relationship between knowledge and data sharing, and the theory of bona fide and fiat objects. We also discuss implementation issues, such as the use of Ontolingua as an ontology editor, and CORBA IDL generator, CORBA, and Java as object platforms. 1 INTROD...